A Compensatory Model for Simultaneously Setting Cutting Scores for Selection-Placement-Mastery Decisions. Research Report 94-17

A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simultaneously. A simultaneous approach has two advantages over separate optimization. First, test scores used in previous decisions can be used as "prior data" in later decisions, increasing the e...

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Bibliographic Details
Main Author Vos, Hans J
Format Report
LanguageEnglish
Published Bibliotheek, Faculty of Educational Science and Technology, University of Twente 01.11.1994
Subjects
Bayesian Statistics
Computer Assisted Instruction
Criteria
Cutting Scores
Decision Making
Evaluation Criteria
Foreign Countries
Mastery Tests
Medical Students
Monotonicity Analysis
Optimization
Scores
Selection
Simultaneous Interpretation
Student Placement
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Summary:A method is proposed for optimizing cutting scores for a selection-placement-mastery problem simultaneously. A simultaneous approach has two advantages over separate optimization. First, test scores used in previous decisions can be used as "prior data" in later decisions, increasing the efficiency of the decisions. Then, more realistic utility structures can be defined using final success criteria in utility functions for earlier decisions. An important distinction is made between weak and strong decision rules. Weak rules are allowed to be a function of prior test scores. Conditions for optimal rules to be monotone are presented, and it is shown that optimal weak monotone rules are compensatory by nature. Results from an empirical example of instructional decision making illustrate the differences between simultaneous and separate approaches. Subjects were 71 medical students receiving interactive video or computer-aided instruction. (Contains 2 tables, 2 figures, and 17 references.) (SLD)